---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-2
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-base-finetuned-gtzan-2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7182
- Accuracy: 0.8

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9471        | 1.0   | 90   | 1.9127          | 0.44     |
| 1.3728        | 2.0   | 180  | 1.4732          | 0.52     |
| 1.4239        | 3.0   | 270  | 1.4735          | 0.55     |
| 0.8211        | 4.0   | 360  | 1.0095          | 0.73     |
| 0.9167        | 5.0   | 450  | 0.8899          | 0.71     |
| 0.5153        | 6.0   | 540  | 0.7832          | 0.76     |
| 0.6258        | 7.0   | 630  | 0.7073          | 0.79     |
| 0.3004        | 8.0   | 720  | 0.6175          | 0.85     |
| 0.2903        | 9.0   | 810  | 0.7182          | 0.8      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1